#Encoder motor driver

[edir2rell]

https://www.futureelectronics.com/p/semiconductors--comm-products--i2c/pca9515adp-118-nxp-7183946

What is I2C communication, serial communication bus, I2C logic

PCA9515A Series 3.6 V 5 mA 400 kHz 6 pF I2C-bus Repeater - SOIC-8

[nmagroup]

Optimizing Performance by Best Practices for PLC Stepper Motor Control Systems

Programmable Logic Controllers (PLCs) are now an integral part of industrial automation. Without a doubt, stepper motor control is one of the most flexible and most important applications among those many. Stepper motors are largely used in manufacturing, robotics, and automations as they offer precise control over position and speed. For effective operation on such systems, though, specific best practices must be followed. Through this guide, we have learned how you can optimize your performance through best practice PLC Stepper Motor Control systems that will allow your automation processes to reach their maximum capabilities.

Understanding PLC Stepper Motor Control

Understanding the best practices also involves understanding the PLC and stepper motor interaction. A stepper motor is a brushless DC motor divided into discrete steps, with precise positional control. A PLC communicates with the motor through driver modules by sending electrical pulses that determine the movement of the motor.

Effective control of these systems can lead to increased accuracy of operation, less consumption of energy, and longer lifespan. This is where optimum performance through best practices for PLC stepper motor control systems comes in handy.

Why Use Stepper Motors with PLCs?

Stepper motors are preferred in automation for several reasons:

Precision: Ideal for applications requiring accurate positioning, such as CNC machines or 3D printers.

Reliability: Durable and capable of maintaining position without continuous power.

Compatibility: Stepper motors work seamlessly with PLCs, allowing integration with other automation systems.

Stepper motors provide many advantages but can still stall, vibrate, or even overheat if their control is not done correctly. For these issues, therefore, look into performance optimization by the best practices of PLC stepper motor control systems.

Best Practices for PLC Stepper Motor Control

1. Proper Selection of Stepper Motor

There are several keys to optimizing your system: First, the stepper motor. Consider the following factors:

Torque and Speed Requirements: The motor must deliver what your application’s operating requirements demand.

Step Angle: A smaller step angle provides for higher resolutions and smoother motion.

Load Capacity: The motor must efficiently handle the weight and inertia of the load.

By choosing a motor that meets your particular needs, you lay the foundation for optimized performance by best practices for PLC stepper motor control systems.

2. Efficient Programming of PLCs

How you program your PLC will make all the difference in system performance. Consider the following aspects while programming:

Pulse Frequency: Tune pulse rates to match motor specs, avoid stalling, or becoming unstable.

Acceleration and Deceleration Ramps: Gradual speed changes minimize mechanical stress on the motor.

Closed-Loop Control: Using feedback systems such as encoders brings about greater precision and error correction.

Good programming practices assure smooth operation and are necessary to optimize performance through best practices for PLC stepper motor control systems.

3. Minimizing Electrical Noise

Electrical noise can cause intercommunication between the PLC and the stepper motor driver to go haywire. For minimizing the noises,

Shield Cables: Use shielded cables, thus protecting signal integrity.

Proper Grounding: Ensure a well-established grounding system for all components.

Separation of Power Lines: Distance signal wires from high-voltage power lines.

These are basic requirements in which to ensure consistent performance and optimize performance by best practice in PLC stepper motor control systems.

4. Regular Maintenance and Inspection

Routine maintenance is also necessary to extend the lifespan of your stepper motor and PLC system. The primary tasks include:

Lubrication: Prevent wear and tear on moving parts.

Tightening Connections: Loose connections can lead to intermittent failures.

Inspecting Wiring: Look for signs of wear or damage in cables.

Maintenance is done consistently in a manner that your system operates on its highest performance, further optimizing performance by best practices for PLC stepper motor control systems.

Enhancing System Efficiency

1. Energy Optimization

Stepper motors consume more power compared to the normal DC motors, and this is especially in holding torque. In order to optimize energy use:

Use a microstepping driver to cut down current at lower speeds.

Implement sleep modes in your PLC program when the motor is idle.

Opt for low power stepper motors when high torque is unnecessary.

Energy-efficient performance means a foundation of optimizing performance by best practices for PLC stepper motor control systems.

2. Integration with Advanced Sensors

Modern PLC systems can integrate with advanced sensors for real-time monitoring and control. Examples include:

Proximity Sensors: Detect the position of objects to trigger motor actions.

Temperature Sensors: Monitor motor temperature to prevent overheating.

Vibration sensors: Identify mechanical issues early.

Sensor integration helps the achievement of automation, improving the PLC stepper motor system by best practices in order to achieve desired performance.

Challenges in PLC Stepper Motor Control

Although stepper motors are reliable, some challenges may appear, such as:

Resonance Issues: Can cause significant vibrations and reduce motor lifespan.

Overheating: Often due to improper settings on current.

Step Loss: It occurs when the motor cannot keep with command pulses.

All these challenges should be addressed by following up the best practices in optimizing performance by the PLC stepper motor control systems.

Conclusion

In the automation world, stepper motors and PLCs will take center stage in providing precision and efficiency. However, the performance in stepper motor control with PLC depends on proper selection, programming, maintenance, and integration with cutting-edge tools. Thus, by perfecting performance with best practices in PLC Stepper Motor Control, you are assured of smoother operations, cost cutting, and longer-lived equipment.

Whether it is a small project in scale or large industrial setup, these practices give a reliable roadmap towards success. Adopt these strategies today and level up in your automation processes!

Originally Published Here:-

[thmhuade]

Essential Guide: How to Drive a Servo Motor Like a Pro

Servo motors have become vital across various industries, from robotics and CNC machinery to automation. Their precision and control make them ideal for applications requiring specific movement or positioning. For those new to the world of servo motors or anyone seeking to sharpen their skills, understanding how to drive a servo motor effectively is key to harnessing its full potential. This guide will walk you through everything you need to know to drive a servo motor like a pro, covering basics, technical tips, and best practices.

What Is a Servo Motor?

A servo motor is a specialized rotary actuator designed for precise control of angular or linear position, velocity, and acceleration. Unlike traditional motors, which typically run at a constant speed, servo motors respond to specific instructions to move to set positions with a high degree of accuracy. They are commonly used in robotics, conveyor systems, camera focus mechanisms, and beyond.

Key Components of a Servo Motor System

To operate a servo motor effectively, it's essential to understand its components:

Motor – The main driver of motion, either DC or AC, that generates rotational movement.

Controller – Sends specific signals to the motor to reach a target position or speed.

Feedback Device – Typically an encoder or potentiometer, providing feedback on the motor's position to ensure accuracy.

Drive Circuit – Interfaces the controller with the motor, enabling controlled power and precise motion.

Step 1: Choose the Right Servo Motor for Your Application

Choosing the right motor type depends on your application's power, speed, and control requirements. Generally, servo motors fall into two main categories:

DC Servo Motors – Better suited for applications requiring lower power and precise control.

AC Servo Motors – More powerful and suitable for higher-speed applications, often used in industrial automation.

Consider the torque, speed, and voltage ratings as you assess which servo motor fits your needs.

Step 2: Understand Control Signals

Servo motors require control signals to determine movement. There are three main types:

Pulse Width Modulation (PWM) – Common in hobbyist and small-scale applications, it involves sending pulses to control motor position.

Analog Signals – Often used in industrial settings, where a specific voltage range controls motor speed or position.

Digital Signals – A more advanced option that communicates precise instructions for accurate control in complex systems.

Step 3: Master the Basics of Servo Motor Controllers

To drive a servo motor effectively, you’ll need a servo controller, the brain behind the operation. It’s responsible for interpreting the commands and converting them into movements. There are two primary control modes:

Position Control – This mode commands the servo to move to a specified position and is highly accurate.

Speed Control – Here, the controller maintains a steady speed, ideal for applications like conveyor belts.

Selecting the right controller based on your application can make all the difference in achieving optimal performance.

Step 4: Set Up Your Servo Drive

The servo drive is an essential component, bridging the motor and controller. Here’s a basic setup guide:

Power Supply – Connect a power source that matches the servo motor’s voltage and current requirements.

Signal Wires – Connect the control signals from your controller to the servo motor input.

Feedback Mechanism – Ensure the encoder or potentiometer is connected to relay accurate positioning data.

Check Connections – Verify all wiring and connections are correct, ensuring stable performance and avoiding overheating or short circuits.

Step 5: Programming Your Servo Motor

Servo motors can be controlled manually or programmed via a microcontroller or PLC (Programmable Logic Controller) for automation. Start by writing basic commands to rotate the motor to specific angles, then proceed to more complex programs for movement sequences. Popular platforms like Arduino and Raspberry Pi are ideal for beginner programmers.

Step 6: Fine-Tuning Performance

To drive a servo motor like a pro, fine-tuning is necessary. Here are some techniques:

PID Tuning – PID (Proportional-Integral-Derivative) controllers are commonly used to fine-tune servo motors, helping achieve smoother and more precise control.

Frequency Response Tuning – Adjusting frequency parameters can prevent oscillations and improve stability.

Gain Adjustment – Increasing or decreasing gain settings affects responsiveness and precision.

Step 7: Troubleshoot Common Servo Motor Issues

When driving a servo motor, issues may arise. Here’s how to troubleshoot:

Inconsistent Positioning – Verify the feedback device is correctly calibrated and connected.

Overheating – Check that the motor isn’t overloaded and that the drive circuit isn’t providing excessive current.

Unexpected Stopping – Inspect connections, power supply, and control signal integrity.

Noise and Vibration – Adjust gain settings or consider a damper if high-frequency noise affects performance.

Step 8: Regular Maintenance

Regular maintenance ensures optimal servo motor performance and extends lifespan. Here are some maintenance tips:

Check Wiring and Connections – Loose connections can cause erratic movements.

Lubricate Bearings – Especially in industrial environments, to prevent wear and tear.

Inspect Feedback Devices – Clean encoders or potentiometers for accurate data.

Why Learn to Drive a Servo Motor Like a Pro?

Mastering servo motor operation enhances productivity, precision, and cost efficiency. Industries benefit from improved control and accuracy in applications ranging from robotics to medical devices, where precise movement can make a crucial difference.

Conclusion

Driving a servo motor may seem complex initially, but with this guide and hands-on practice, you'll be able to control it confidently. Whether you’re aiming for exact positioning or consistent speed, mastering servo motors will open up opportunities for innovation and efficiency.

[saas22inc]

The Road to Reliable AI with Hamming CEO, Sumanyu Sharma

TL;DR: Sumanyu Sharma is the Founder & CEO of AI startup, Hamming. He’s been obsessed with AI forever—from academic research to production systems at Tesla—and he has an uncommonly well-rounded view of what it takes to make AI actually work. In this wide-ranging interview, Sumanyu shares how Hamming is tackling the key challenges of AI reliability through prompt tuning, evaluation, and observability. He also dives into the thorny questions around governing AI's risks and societal impacts. Read Sumanyu's interview for a nuanced take on what responsible AI development looks like and why reliability is the key to unlocking the technology's full potential.

Sumanyu, thanks for making the time to do this. Let's kick things off with how you first got hooked on AI - was there a lightbulb moment that set you on this path or was it a gradual build up?

I've always been fascinated by systems that learn and improve with more data or repetition, whether it's human or AI systems. As a kid, I used spaced repetition techniques to retain information better and optimize my own learning. This early interest in self-optimization set the stage for my passion for AI. During my undergrad at the University of Waterloo, I got my first taste of real-world AI—back then it was called machine learning.

“My "aha" moment came when I took Andrew Ng's class on Coursera and built a hand digit classifier that actually worked. It was incredible to see that machines can learn and improve with more data, just like humans.”

The realization that I could build systems capable of learning and adapting on their own was a game-changer for me. Since then, I've been hooked on systems that get better with more data. I took courses to learn the fundamentals of AI, pursued internships to gain practical experience, and worked with research groups at my university to dive into academic research.

I was fortunate to drive massive business outcomes using AI at Tesla and later at Citizen, sometimes with simple models, sometimes with complex ones.

When ChatGPT launched, I became obsessed with how LLMs work and what they can do, quickly becoming a daily active user and a power user. The pace of improvement in the AI space since then has been breathtaking.

At places like Tesla, Citizen, or even back in college - what were some of the key experiences that made you recognize the need for more reliable AI systems?

“Lack of reliability has always been the #1 issue limiting the widespread use of machine learning across various fields. Generative AI is just a new flavour of an old problem.”

During my time at the University of Waterloo, I aimed to help radiologists diagnose patients more accurately and quickly by leveraging past records of similar X-rays. This idea seemed obviously useful, but achieving reliable results was challenging. We developed a feature extraction technique by stacking auto-encoders into binary vectors to semantically search for similar medical images. While we got results good enough to post an arXiv paper, they weren't reliable enough for clinical settings, where a misdiagnosis could harm real patients. This experience highlighted the gap between academic success and real-world reliability, underscoring the need for more robust AI systems.

At Tesla, I encountered a similar issue but on a larger scale. Humans are terrible drivers—94% of motor vehicle accidents are caused by driver error. Building Level 5 autonomy could save thousands of lives each year. It took Waymo eight years to develop a system reliable enough for production. Tesla's approach is different but still not reliable enough for use without human supervision. Working on these projects made it clear how crucial reliability is for AI applications that impact human lives. The stakes are incredibly high, and any system that isn't 100% reliable can't be trusted to operate autonomously in critical situations.

I believe current multi-modal models face similar reliability challenges as early autonomous systems. While foundational models continue to improve, there remains a significant gap between their raw capabilities and the ability to translate these capabilities into reliable AI products and services.

“Businesses need AI systems that can consistently deliver accurate results in real-world conditions, not just in controlled environments or simulations.”

Moreover, this reliability gap isn't just a technical issue but also a matter of trust. Users need to trust that AI systems will perform as expected without causing unintended harm. This trust is built through rigorous testing, transparent operations, and continuous improvement. As AI systems become more integrated into our daily lives, ensuring their reliability will be paramount.

Your background spans publishing AI research, product leadership, leading data science teams, and driving strategic initiatives. How did wearing all those hats shape your approach and priorities at Hamming?

Well, I've been fortunate to have a diverse background.

Having done research in medical image search and deep learning, I have some intuition for fruitful research-oriented work streams. For example, we recently benchmarked major LLMs—GPT-4, Opus, Gemini 1.5 Pro, and Llama 3 70B—on codegen tasks by partnering with the University of Waterloo. This study was pretty popular on Reddit and within the YC community, and we plan to do more work like this.

My background in growth and data also provides a sixth sense of the growth rates we need to hit, what's realistic for fundraising and internal planning, as well as how to properly impact size and prioritize new features as Hamming scales.

And having been an engineer, I have a decent grasp of the engineering talent required at each stage, making collaboration with our technical team that much smoother without heavily relying on external judgement.

“I would be a significantly worse CEO without the critical skills I learned along the way before co-founding Hamming.”

Because I have a deep understanding of the entire product, engineering, research, and go-to-market landscape, I can make decisions quickly and decisively.

Can you walk us through the early days of founding Hamming? What were the biggest challenges in going from an innovative idea to an actual product and business?

The core idea for Hamming started from an evals script I wrote to solve a customer's pain point when building their RAG pipeline. The goal was to make changes to any part of the retrieval pipeline and get quantitative feedback on metrics like accuracy, hallucinations, and latency in minutes—unlike the typical vibe-checking outputs on a handful of examples in a prompt playground.

I found myself spending more time fixing the script, which was supposed to accelerate my feedback loop, than doing the actual work. This felt unusually hard, and I realized others must be experiencing the same problem.

So, I teamed up with Marius, my co-founder and CTO, to build a platform to solve this problem more comprehensively. This was definitely a "scratch your own itch" founding story.

Going from zero to one is brutal. Everything is manual, and there are no A/B tests because you don't have enough users. You have to do things that don't scale to get a handful of paying customers and do everything possible to make them love your product.

“My conviction in the problem space grows with every user I speak to. Most teams tell me that reliability is the #1 concern stopping them from shipping AI products to their customers.”

We've shipped prompt tuning, evaluation, and observability, but there's a lot more to do. We're releasing a new product every month, each tackling a different aspect of reliability.

It seems your platform components—prompt tuning, evaluation, and observability—form a cohesive solution. Can you give us an overview of how they work together to increase AI reliability for enterprises?

That's right. Prompt tuning, evaluation, and observability work together to drive reliability in a piecewise fashion.

Most teams start by writing basic prompts to quickly prototype a solution to their problem. It's easy to get 60% of the results with 20% of the effort.

“Improving prompts from 60% to 95% is extremely painful. Our prompt tuner samples the prompt solution space, tries hundreds of new prompts, and quickly returns the optimal prompt with its quantitative performance on a dataset.”

This prompt tuning heavily relies on evaluation to find the best prompts. As you move beyond prompts, you'll find it's challenging to improve the retrieval performance of RAG-based systems. RAG systems can fail during retrieval (failing to fetch the correct documents) or reasoning (failing to reason with the correct documents passed to the LLM).

We've built RAG-specific model-based evaluators that help teams differentiate between these error types. This allows teams to focus on improving their retrieval pipeline if retrieval is the bottleneck or their prompts if hallucinations are the primary issue.

Similarly, tool use is often unreliable when building AI agents. Common failure modes include improper arguments returned, wrong functions called, or hallucinated functions/parameters. We've built a function definition optimizer that tests different function call definitions to get the best results.

The combination of prompt tuning, RAG evaluations, and function definition optimization saves teams hundreds of hours per week during development. As you launch your AI products into production, you need to deeply understand how users are interacting with them beyond just token usage, latency, and other basic metrics.

Our observability tools provide this insight, helping you ensure ongoing reliability and user satisfaction.

One of your key value propositions is "reliable AI in weeks" vs months. What core innovations allow for such a rapid development cycle?

“The biggest bottleneck in building reliable AI systems comes from having humans in the loop. Without LLMs to speed up iteration velocity, making changes to your prompt, retrieval pipeline, or function definition, requires a human to check if the change improved accuracy or increased hallucinations. But humans are slow, expensive, and unreliable.”

It's impossible for a human to check every single edge case by hand. As a result, you can run a maximum of 2-3 experiments per week with this human-in-the-loop approach. This is why most AI products take months or even years to become reliable enough for teams to feel comfortable shipping. Even after shipping something to production, teams are nervous about making changes that could cause regressions for end customers.

LLMs, however, are great at reasoning and can measure accuracy, tone, hallucinations, and other quality metrics 20 times cheaper and 10 times faster than humans. LLMs will only continue to get smarter, making iteration feedback cycles even faster.

“By using LLMs as judges and leveraging them to generate optimized prompts and function definitions, teams can run 10 experiments per day.”

We spend a lot of time fine-tuning LLM evaluators to model human preferences because an LLM's definition of good may not be the same as a human's. We work closely with each customer to build their own custom evaluators to ensure the highest accuracy and relevance.

This ability to rapidly iterate and improve using LLMs is what allows us to deliver reliable AI in weeks rather than months. By automating the evaluation process and optimizing every step of the development cycle, we significantly cut down the time required to achieve robust, reliable AI systems.

I'm interested in hearing more about Hamming's prompt tuning capabilities. How does auto-generating optimized prompts improve performance vs manual approaches?

Writing high-quality and performant prompts by hand requires enormous trial and error. Here's the usual workflow:

Write an initial prompt.

Measure how well it performs on a few examples in a prompt playground.

Tweak the prompt by hand to handle cases where it's failing.

Repeat steps 2 & 3 until you get tired of wordsmithing.

What's worse, new model versions often break previously working prompts. Or, say you want to switch from OpenAI GPT3.5 Turbo to Llama 3. You need to re-optimize your prompts by hand.

Our take: use LLMs to write optimized prompts for other LLMs.

Describe the task you want to accomplish.

Add examples of input/output pairs that best describe the task.

Start optimizing.

Behind the scenes, we use LLMs to generate different prompt variants. We use an LLM judge to measure how well a particular prompt solves the task by measuring performance on the input/output pairs you described. We capture outlier examples and use them to improve the few-shot examples in the prompt. We run several "trials" to refine the prompts iteratively.

This is very similar to how metaheuristic optimization algorithms like genetic algorithms and simulated annealing find global optimal solutions by intelligently sampling the search space. The benefits are obvious.

“No more tedious wordsmith-ing. No more scoring outputs by hand. No need to remember to tip your LLM or ask it to think carefully step-by-step. Using LLMs to auto-generate optimized prompts drastically improves performance compared to manual approaches, saving you time and effort while ensuring consistent, high-quality results.”

Shifting gears to a more tactical question - as a founder, I'm sure you've leveraged many SaaS tools to power Hamming's growth and operations. Across customer experience, employee engagement, sales intelligence, productivity, and security - what have been some of your favorite tools that you consider indispensable in your stack? Any hidden gems more founders should know about?

We love supporting other YC companies, and we use a variety of SaaS tools to power Hamming's growth and operations. Here are some of our favorites across different areas:

Customer Support: We use Atlas (YC) for customer support. It's been a game-changer for managing customer interactions.

Sales Intelligence: For sales, we use a combination of Apollo (YC), LinkedIn, and Dripify. This mix helps us talk to people who care about what we're building.

Productivity: I'm a huge fan of Superhuman for emails—it makes managing my inbox a breeze. Superwhisper is great for speech-to-text, Warp (an AI-first terminal) saves me time from having to remember bash commands, and Cursor (an AI-first VSCode fork) makes our eng team at least 3x faster. For task management, I rely on Sunsama for personal tasks and Linear for managing engineering tasks.

Code Management: We use Greptile (YC) for semantically searching across our entire codebase and automating PR reviews, and Ellipsis (YC) for additional PR review support.

Documentation: Mintlify (YC) is our go-to for documentation. It makes creating and maintaining high-quality docs easy and efficient.

These tools are indispensable in our stack, and I highly recommend them to other founders. They help us stay productive, organized, and focused on what matters most - talking to customers and making something people want.

Talent capable of building robust AI products is liquid gold—expensive and in high-demand. How has Hamming been able to attract and retain a high caliber team despite this challenge?

You're totally right. At Hamming, we've been fortunate to attract and retain a talented team so far by emphasizing our mission and creating a culture of complete freedom and ownership.

Our team is passionate about making AI reliable for all enterprises. There's no silver bullet to reliability—we need to solve many problems along the way to achieve this goal. Our internal success criteria is for every enterprise to use Hamming to build AI products. The team won't stop until we get there.

Many organizations are extremely top-down, with CEOs pushing half-baked ideas down the product and engineering teams' throats. At Hamming, we believe the best ideas come from within the organization and from insights gained by talking to customers. This is especially true in our space, where the market is changing rapidly.

“Anyone in our org can propose an idea, show why it's a good idea, how many customers it can impact, and then execute on it without needing top-down buy-in from me or anyone else.”

This inclusive and empowering culture drives our success and keeps our team motivated and engaged.

And with great freedom comes total ownership. When someone executes an idea and it doesn't work, they take complete ownership of the outcome, and propose a plan to either wind it down or present new adjacent ideas based on what they learned.

The combination of having a compelling mission and a culture that treats people like adults that keeps our team grinding every single day, seven days a week.

Unreliable AI systems can lead to serious issues like the Air Canada chatbot incident. What processes or guardrails does Hamming have to prevent such brand risks or violations of business policies?

Absolutely. That was a huge wake-up call for enterprises using the "move fast and break things" mentality to ship unreliable AI products. Another instance was New York City's "MyCity" AI chatbot, which ended up hallucinating and accidentally telling users to break the law.

For example, when asked if an employer can take a portion of their employees' tips, the bot responded affirmatively, despite the law stating that bosses are not allowed to take employee tips.

Preventing brand risks and violations of business policies requires a comprehensive, multi-pronged approach. Here's how we tackle it at Hamming:

Prompt Reliability: Every prompt in your system needs to be reliable, version-controlled, and audited for robustness against prompt injection attacks. Our prompt tuning product helps businesses create prompts that are more reliable and less susceptible to such attacks.

Evaluation for RAG & AI Agents: Our evaluation solution helps teams measure and minimize hallucinations during development. Every time a team makes a change to the prompt or retrieval pipeline, they can rely on Hamming to detect regressions and identify areas for improvement.

Proactive Red-Teaming: We conduct proactive red-teaming on existing AI systems to test their resilience against known prompt injection attacks or malicious inputs. This adds an extra layer of safety before teams deploy their products to production.

Guardrails: We're currently building AI guardrails that act as an internal firewall, preventing unwanted, harmful, or inaccurate statements from ever reaching your end users.

“By making prompts resilient, using evaluations to measure and minimize hallucinations, proactively red-teaming to ensure robustness against prompt injection attacks, and using guardrails as a final firewall, enterprises can safely deploy their AI products to production and keep them secure.”

You've described 2023 as the "year of demos" and 2024 as the "year of reliability". Looking ahead, what do you see as the next frontier or major challenge facing widespread enterprise AI adoption in 2025 and beyond?

I think reliability will continue to be a challenge in 2025 and beyond. The shape of 'reliability' will evolve—what's hard today may be easier tomorrow, but new attack vectors will emerge. For example, most LLMs are trained on publicly available data, often scraped from websites. A rogue actor, possibly a government, could create poisoned datasets to corrupt the pre-training process and subtly bias model outputs. I recently learned about a front-running poisoning technique targeting web-scale datasets that periodically snapshot crowdsourced content—such as Wikipedia—where an attacker only needs a time-limited window to inject malicious examples. We'll need new solutions to check the integrity of the datasets used to train LLMs.

Governance will also be a significant challenge. As AI models become more powerful and ubiquitous, enterprises will face increased scrutiny to ensure their AI systems are used safely, ethically, and without bias.

“Regulatory frameworks will likely become more stringent, requiring companies to demonstrate compliance with new standards. And this regulatory burden‌ could introduce significant friction, making it harder to innovate rapidly.”

Organizations will need robust governance frameworks to manage compliance while still fostering innovation. Ensuring AI operates ethically and without bias will be paramount. As AI systems influence more aspects of society, the demand for transparency and accountability will grow.

Enterprises will need to implement comprehensive bias detection and mitigation strategies, ensuring their AI models do not perpetuate existing inequalities or introduce new biases. Developing explainable AI (XAI) will be crucial to provide insights into how models make decisions, thereby building trust with users and regulators.

Security and privacy concerns will also be more pronounced. Protecting sensitive data from breaches and ensuring individual privacy will be critical. AI systems must be robust against adversarial attacks, where malicious actors attempt to deceive or manipulate AI behavior. Strong security measures and maintaining data privacy will be essential to safeguard both the technology and its users.

Finally, the environmental impact of large-scale AI deployments, particularly the energy consumption of training and running complex models, will become a significant concern. Enterprises will need to adopt more sustainable practices, such as optimizing algorithms for efficiency and leveraging green computing resources. Balancing the benefits of AI with its environmental footprint will be a key consideration for future AI strategies.

As Hamming deploys AI systems at scale there's power - but also responsibility. What's your take on governing the ethical risks and societal impacts of such powerful technologies?

Deploying AI systems at scale comes with significant responsibility. AI has the potential to revolutionize industries and improve lives, but it may also displace millions of jobs. As research teams advance foundational models, everyone is learning and adapting to this new reality. While I don't have deep expertise in risk mitigation, I can offer a few ideas.

Firstly, transparency is crucial. Our AI systems must be explainable, providing clear insights into how decisions are made. This builds trust with users and regulators, ensuring our technology isn't a black box but a tool that can be understood and scrutinized. I admire the work Anthropic has done in making their models more explainable and easier to trust.

Secondly, we need robust frameworks to detect and mitigate bias. AI systems should not perpetuate existing inequalities or introduce new biases. Continuous monitoring helps detect and address biases as they emerge. Beyond technical solutions, fostering a diverse team with contrarian opinions is essential in managing these risks.

Thirdly, privacy and security are non-negotiable. Protecting sensitive data from breaches and ensuring individual privacy will become even more important.

Fourth, on the regulation side, we need to create robust frameworks that balance the need for innovation with the imperatives of safety and ethics.

In essence, governing the ethical risks and societal impacts of AI requires a multi-faceted approach. At Hamming, we are committed to building not just powerful AI systems, but responsible ones.

What responsibilities do you believe AI companies should have in terms of pressure-testing for biases, discrimination, or potential harms before releasing systems?

Both foundational AI companies and application-focused AI companies have an enormous responsibility to ensure their systems are thoroughly pressure-tested for biases, discrimination, and potential harms before release.

At Hamming, our evaluation, continuous monitoring, and red-teaming services rigorously evaluate models and AI systems for any signs of bias or discrimination. We use diverse datasets that reflect the real-world scenarios our customers' systems will encounter. By simulating various edge cases and stress-testing the models in controlled environments, we can identify and mitigate risks early on.

Secondly, transparency and alignment are key. The more we understand about how these AI systems work, the better we can align them to reflect human preferences, confidently eliminating bias, discrimination, and other potential harms.

Moreover, continuous monitoring post-deployment is essential. Implementing feedback loops to measure real-world performance ensures that the systems remain fair and effective over time.

At Hamming, we take pressure-testing for biases, discrimination, and potential harms seriously. By doing so, we can ensure that our AI systems are not only powerful but also just and beneficial to all.

Looking 5-10 years out, what types of guardrails—whether regulation, compliance, dynamic monitoring, or other safeguards—do you believe will be critical for responsible AI development?

Looking 5-10 years out, the most exciting AI use cases are in regulated industries like healthcare, financial services, and law. All four areas you mentioned—regulation, compliance, dynamic monitoring, and guardrails—are crucial for using AI safely, fairly, and without systemic bias.

Firstly, we need a sensible regulation framework. As AI systems become more integrated into critical sectors, clear and enforceable regulations will help ensure these technologies are developed and deployed responsibly. Regulations should focus on transparency, accountability, and fairness, setting standards that are logical and don't slow down innovation too much.

Compliance is equally important. AI companies must develop and maintain comprehensive compliance programs that align with regulatory requirements. This includes regular audits, documentation, and adherence to best practices to ensure ongoing compliance.

Dynamic monitoring will be crucial for maintaining the integrity and reliability of AI systems. We continuously monitor, detect, and mitigate potential biases, errors, or malicious activities on behalf of our customers before they cause harm.

Guardrails, including ethical guidelines and operational safeguards, are necessary to guide AI development. These guardrails should be embedded throughout the AI lifecycle, from design to deployment.

Additionally, fostering a culture of responsibility within AI companies is pretty vital. Education and training programs that emphasize ethical AI development, coupled with a commitment to transparency and accountability, will help build a foundation for responsible innovation. Encouraging collaboration with external stakeholders, including policymakers, ethicists, and the public, will further strengthen the guardrails around AI development.

We've covered a lot of ground today. Before we wrap up, is there anything else you'd like to add or emphasize in terms of Hamming's mission and the future you envision? What final thoughts can you leave us with?

Our mission is making AI reliable.

“We believe every company is already an AI company or will become an AI company in the future.”

We imagine a world where we can help every enterprise build self-improving and reliable systems that unlock trillions in economic value and significantly speed up innovation in all areas - especially science and technology.

[stepperonline52]

How to improve the accuracy of closed-loop stepper motors

1.What is the role of closed-loop stepper motors The role of closed-loop stepper motors mainly includes high-precision position and speed control, improving the response speed and acceleration performance of the system, enhancing the load capacity and efficiency of the system, and achieving low-noise and low-vibration operation. ‌ Closed-loop stepper motors achieve high-precision position and speed control by introducing position feedback and speed feedback, which significantly improves the control accuracy and stability of the entire system. This feedback mechanism enables the closed-loop stepper motor to respond to operating instructions more quickly, thereby improving the response speed and acceleration performance of the system. In addition, by better controlling the speed and acceleration of the motor, the closed-loop stepper motor enhances the load capacity of the system and improves the efficiency of the system. Finally, due to the ability to better control the operation of the motor, the closed-loop stepper motor achieves low-noise and low-vibration operation, thereby improving the reliability and stability of the entire system.

2.Working principle of closed-loop stepper motors The closed-loop stepper motor is an intelligent drive device that is widely used in the fields of machinery, automation, and electronic equipment. Its working principle is based on magnetic field interaction and current application. Specifically, when the external driver sends a control signal to the motor, the motor changes the current according to the signal to achieve rotation. At the same time, the encoder inside the closed-loop stepper motor monitors the position of the rotor in real time and feeds this information back to the control system. The control system precisely controls and positions the motor based on the information provided by the encoder, thereby achieving high-precision motion control. This closed-loop control method enables closed-loop stepper motors to have the advantages of high precision, high speed, and high reliability, and can accurately control the position and speed of the rotor, thereby achieving high-precision positioning and motion control. Compared with traditional open-loop stepper motors, closed-loop stepper motors achieve more accurate position feedback and control system adjustment through internal encoders, providing higher positioning accuracy and more reliable performance.

3.Precautions for using closed-loop stepper motors ‌1.Correctly connect the line sequence of the encoder and the stepper motor. Make sure that the line sequence of A+, A-, B+, and B- is correctly connected to avoid the "Phase Line Error!" error. If this error occurs, the line sequence of the motor should be readjusted after power off. ‌2.Keep the drive well ventilated. The drive of the stepper motor is not sealed, so care should be taken to ensure good ventilation during use to avoid overheating damage caused by long-term operation. ‌3.Prevent metal shavings and dust from falling into the driver. Since the driver board of the stepper motor is not sealed, metal shavings and dust should be prevented from falling into it during use to prevent short circuits and motor damage. ‌4.Pay attention to the positive and negative connections of the power supply. When plugging in the power supply, be sure to pay attention to the correct connection of the positive and negative labels to avoid burning the driver due to incorrect positive and negative connections. ‌5.Connect the basic system step by step. When connecting the circuit of the stepper motor, do not connect all the circuits at the beginning. You should gradually connect them into the most basic system, and then gradually increase the connection after confirming that it is running well. ‌6.Observe the state of the motor. Within half an hour of starting to run, you should closely observe the state of the stepper motor, such as whether the movement is normal, the sound and the temperature rise. If you find any problems, you should stop and adjust them immediately.

4.Ways to improve the accuracy of closed-loop stepper motors ‌1.Hardware connection and encoder installation: By installing an encoder, the stepper motor can achieve full closed-loop control and improve positioning accuracy. The use of encoders can be based on the segmentation requirements, with different levels of resolution, for real-time feedback, thereby achieving precise control of the stepper motor. ‌2.Origin control: According to the Z signal of the encoder, the coordinate origin is identified and calculated. In this way, the accuracy can reach a certain standard, ensuring that the stepper motor can accurately return to or locate to the specified origin position. 3.Out-of-step control: According to the feedback data of the encoder, the output pulse is adjusted in real time, and corresponding out-of-step adjustment measures are taken to ensure the stable operation and precise position control of the stepper motor. ‌4.Optimized current control method: Through PWM control and current attenuation mode, the step error problem under low-speed operation or positioning control, as well as the torque instability problem under high-speed operation, are solved, thereby improving the operation quality and positioning accuracy of the stepper motor. ‌5.Reduce the step angle and increase the number of beats: The accuracy of the stepper motor can be increased by reducing the step angle or increasing the number of beats. When the double beat system is adopted, the step angle is reduced by half, thereby improving the working accuracy. ‌6.Increase the number of rotor teeth‌: Increasing the number of rotor teeth can also reduce the step angle, thereby reducing the error of motor operation and improving positioning accuracy‌.

Source:https://olgana.pixnet.net/blog/post/163203529

[stepper1128]

How to adjust the dip switch of the stepper motor driver

1.Explanation of stepper motor driver The stepper motor driver is an actuator that converts electrical pulses into angular displacement, which is mainly used to control the rotation and movement of the stepper motor. It realizes the drive of the motor by converting the control signal into the drive signal of the motor. The stepper motor driver is generally composed of a pulse generator, a power module, a signal decoder and a drive module. The pulse generator is used to generate a control signal (pulse signal) to control the movement of the motor; the power module provides power to the motor so that the motor can operate normally; the signal decoder converts the pulse signal into a motor drive signal to control the operation of the motor; the drive module is used to amplify the motor drive signal to provide sufficient power to drive the motor. ‌

2.Classification of stepper motor drivers 1.Voltage driver: It controls the speed and position of the stepper motor by changing the drive voltage. This driver is characterized by simple structure and low cost, but poor dynamic performance, easy to heat up and lose step. ‌2.Constant current driver: It drives the stepper motor by controlling the current to ensure that the current of the motor remains constant during operation. This type of driver is characterized by good dynamic performance and low heat generation, but the structure is relatively complex and the cost is high. ‌3.Microstep driver‌: It is a high-precision drive method that achieves more detailed position control by dividing the basic step of the stepper motor. This driver has the characteristics of high precision, low vibration and low noise, and is suitable for application scenarios with high precision requirements. ‌4.Closed-loop driver‌: By adding an encoder or other sensor to achieve real-time feedback on the position of the stepper motor, high-precision position control is achieved. This driver has the characteristics of high precision, high dynamic performance and low step loss rate, but the structure is relatively complex and the cost is high.

3.Reasons for stepper motor driver alarm 1.Power supply problems‌ are one of the common reasons for stepper motor driver alarms. This includes unstable power supply voltage, too high or too low power supply voltage, poor power supply line contact, and power switch failure. Solutions to these problems include checking whether the power supply voltage meets the requirements, adjusting the power supply voltage in time, repairing or replacing the power supply line contact, and checking and replacing the power switch‌. 2.Motor problems‌ may also cause stepper motor driver alarms, including motor damage, poor contact between the rotor and stator, and winding short circuit. Solutions to motor failures may include checking whether the motor is overheating and whether it needs to be replaced or maintained, such as cleaning and lubrication. 3.Control signal problems are also an important factor, including poor contact of the control signal line, controller failure, and unstable control signal voltage. Solutions to these problems may involve repairing or replacing the control signal line, checking and replacing the controller, and adjusting the control signal voltage. 4.Problems with the driver itself, such as a damaged or improperly adjusted driver, can also cause alarms. Solving these problems may require replacing the driver or adjusting the driver settings.

4.How to adjust the stepper motor driver dip switch 1.Understand the basic principles of stepper motor drivers A stepper motor driver is an electronic device used to control stepper motors. It converts current into signals that the stepper motor can understand, thereby driving the motor to rotate precisely. Before adjusting the dip switch, you need to understand the basic principles of the stepper motor driver. 2.Determine the working mode and parameter settings Before adjusting the dip switch of the stepper motor driver, you first need to determine the working mode and parameter settings. The working mode can be full-step mode, half-step mode or micro-step mode; parameter settings include step angle, acceleration, drive current, etc. 3.Consult the instruction manual of the stepper motor driver Stepper motor drivers are usually equipped with an instruction manual, which contains detailed parameter settings and information about the dip switches. Before making adjustments, read the instruction manual carefully to understand the location and corresponding functions of the dip switches. 4.Locate and adjust the dip switches According to the instruction manual of the stepper motor driver, locate the dip switches on the driver. Dip switches are usually a row of small switches that can be set to different functions and parameters by toggling. Before adjusting the dip switches, it is recommended to turn off the power supply to avoid short circuits or other damage to the circuit. 5.Adjust the dip switches as needed Adjust the dip switches from one position to another as needed. When adjusting the dip switches, carefully check the information in the instruction manual to ensure that they are adjusted to the correct position. Some dip switches may have multiple options, while others may only have two options (on/off). 6.Start and test the stepper motor driver After the adjustment is completed, reconnect the power supply and start the stepper motor driver. According to the working mode and parameter settings of the driver, perform corresponding tests to ensure that the motor can rotate as expected. If other parameters need to be adjusted, you can refer to the instruction manual again and repeat the above steps. 7.Test and application of the adjusted stepper motor driver Once the dip switches of the stepper motor driver are successfully adjusted, some tests and practical applications can be performed. In the test, you can verify whether the set working mode and parameters are as expected. In the application, you can connect the stepper motor driver to the corresponding equipment or system to achieve the desired functions and performance.

Source:https://www.steppernews.com/2024/09/how-to-adjust-dip-switch-of-stepper.html

[sarveshr]

Gantry System / CNC Auto Loader / Robotic Automation / CNC Lathe Automation

Grey Matter Robotics Pvt. Ltd. is a leading industrial robotics automation company from India, with a proven track record of over 150 successful turnkey projects. We specialize in developing pick & place applications using gantry systems and 6-axis robotic arms. With a strong commitment to quality, we deliver top-notch industrial robotics and automation solutions to clients worldwide.

A top company specializing in gantry systems and gantry robots for CNC machine tending applications.

Understanding CNC Machines: An In-Depth Look at Their Components

CNC (computer numerical control) machines are sophisticated pieces of equipment designed to automate the manufacturing of parts from a variety of materials, including metal, plastic, and wood. These machines come in various configurations, with CNC mills and CNC lathes being the most common. CNC lathes are ideal for processing cylindrical parts, while mills are versatile enough to handle flat, curved, or angular parts.

This article will explore the different components of a CNC machine. Some parts are common to both lathes and mills, such as the control unit, driving system, and feedback system, while others are specific to certain types of machines. For instance, tailstocks and headstocks are unique to CNC lathes.

1. Input Device

The input device is how CNC programs are loaded into the machine. This can be done through a keyboard (to directly input G-code commands), a USB flash drive (to transfer a program from another computer), or wireless communication (to download a program from another computer over a network).

2. Machine Control Unit (MCU)

The MCU is the brain of the CNC machine. It comprises electronic hardware and software that interpret the G-code provided by the input device and translate it into instructions for the tool drivers. The MCU controls the movements of servo motors along the machine’s axes and processes feedback from sensors to ensure precise tool positioning. It also manages tool changers and coolant activation as specified by the G-code.

3. Machine Tools

Machine tools refer to any tools that perform processes on a workpiece, usually cutting tools. CNC lathes use stationary tools and rotate the raw material to make cuts, whereas CNC mills move spinning tools into stationary material. Advanced 5-axis machines can move both the tool and the workpiece, enabling the creation of more complex features. Machine tools are stored in “tool libraries,” and a tool changer automates the swapping of tools during operations.

4. Driving System

The driving system consists of the motors that move the tool along the machine’s axes. In a standard CNC mill, the bed moves horizontally along the x- and y-axes, while the cutting tool moves up and down along the z-axis. In a CNC lathe, the driving system moves the cutting tool along the rotational axis of the workpiece. Movement is often controlled by servo motors, ball screws, and linear guides to ensure precision.

5. Feedback System

A feedback system is essential for maintaining accuracy. It uses a closed-loop control system to verify and adjust the position of mechanical components after movement. This can be achieved with linear or rotary encoders attached to the servo motors. Special probing tools are also used to measure the actual part during machining, ensuring dimensional accuracy.

6. Display Unit

The display unit is a screen that shows crucial information to the operator. Some units have large, high-resolution screens displaying extensive data, while others have smaller, low-resolution screens showing only essential information. The display unit allows the operator to input G-code, change machine settings, and monitor the machine’s status.

7. Bed

The bed of a CNC mill is where the raw material is mounted. Various work-holding jigs secure the workpiece in place, often using t-slots or holes for attachment. In a CNC lathe, the tool turret and tailstock are mounted to the bed, and the raw material is secured in the chuck.

8. Headstock

The headstock is specific to lathes and contains the main drive, bearings, and gears needed to rotate the chuck. Located on the left side of the lathe, the headstock is usually enclosed and accessed via removable panels.

9. Tailstock

The tailstock supports long, cylindrical workpieces on one side while the chuck supports the other, preventing deflection during cutting. The tailstock can move along the lathe’s z-axis to accommodate different lengths of raw material.

10. Tailstock Quill

The tailstock quill, located in the tailstock, has a conical end aligned with the spindle and chuck axis. It provides additional support for long shafts by fitting into a drilled hole in the workpiece, with limited range of motion adjusted by pneumatic or hydraulic pressure.

11. Footswitch or Pedal

Foot pedals are used in CNC lathes to activate and deactivate the chuck and tailstock quill, allowing operators to load and unload parts easily. CNC mills typically do not have foot pedals, as the parts are already supported on the bed.

12. Chuck

The chuck is a lathe-specific component that grips the raw material during machining. It rotates at high speed and typically has three or four pneumatically or hydraulically actuated grips. Three-jaw chucks are self-centering, while four-jaw chucks can be individually adjusted for greater accuracy and eccentric cutting.

13. Control Panel

The control panel includes the input device, display unit, keyboard, and other controls for interacting with the CNC machine. It is often attached to the machine with an extendable arm, allowing operators to position it conveniently.

This comprehensive look at CNC machine components highlights the complexity and precision involved in modern manufacturing processes, ensuring high-quality, accurate production across various industries.

3 & 4-axis gantry systems, gantry robots, Cartesian robots, linear stages, robot tracks, and linear axes

Leveraging our expertise in developing and manufacturing 3 and 4-axis gantry systems, we deliver exceptional automation solutions for CNC machine loading and unloading. Our gantry systems boast high payload capacities and high-speed capabilities, ensuring efficient and streamlined operations. Built with a robust structure for enhanced stability, our gantry systems are designed to be user-friendly, boosting productivity. Furthermore, they require minimal maintenance, making them a reliable and cost-effective option for CNC machine automation.

[trendingreportz]

Field Programmable Gate Array (FPGA) Market - Forecast(2024 - 2030)

The FPGA market was valued at USD 4.79 Billion in 2017 and is anticipated to grow at a CAGR of 8.5% during 2017 and 2023. The growing demand for advanced driver-assistance systems (ADAS), the growth of IoT and reduction in time-to-market are the key driving factors for the FPGA market. Owing to benefits such as increasing the performance, early time to market, replacing glue logic, reducing number of PCB spins, and reducing number of parts of PCB, field programmable gate arrays (FPGA’s) are being used in many CPU’s. Industrial networking, industrial motor control, industrial control applications, machine vision, video surveillance make use of different families of FPGA’s.

North America is the leading market for field programmable gate arrays with U.S. leading the charge followed by Europe. North America region is forecast to have highest growth in the next few years due to growing adoption of field programmable gate arrays.

What is Field Programmable Gate Arrays?

Field Programmable Gate Arrays (FPGAs) are semiconductor devices. The lookup table (LUT) is the basic block in every FPGA. Different FPGAs use variable sized LUTs. A lookup table is logically equivalent to a RAM with the inputs being the address select lines and can have multiple outputs in order to get two Boolean functions of the same inputs thus doubling the number of configuration bits. FPGAs can be reprogrammed to desired application or functionality requirements after manufacturing. This differentiates FPGAs from Application Specific Integrated Circuits (ASICs) although they help in ASIC designing itself, which are custom manufactured for specific design tasks. 

In a single integrated circuit (IC) chip of FPGA, millions of logic gates can be incorporated. Hence, a single FPGA can replace thousands of discrete components. FPGAs are an ideal fit for many different markets due to their programmability. Ever-changing technology combined with introduction of new product portfolio is the major drivers for this industry.

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What are the major applications for Field Programmable Gate Arrays?

FPGA applications are found in Industrial, Medical, Scientific Instruments, security systems, Video & Image Processing, Wired Communications, Wireless Communications, Aerospace and Defense, Medical Electronics, Audio, Automotive, Broadcast, Consumer Electronics, Distributed Monetary Systems, Data and Computer Centers and many more verticals.

Particularly in the fields of computer hardware emulation, integrating multiple SPLDs, voice recognition, cryptography, filtering and communication encoding,  digital signal processing, bioinformatics, device controllers, software-defined radio, random logic, ASIC prototyping, medical imaging, or any other electronic processing FGPAs are implied because of their capability of being programmable according to requirement. FPGAs have gained popularity over the past decade because they are useful for a wide range of applications.

FPGAs are implied for those applications in particular where the production volume is small. For low-volume applications, the leading companies pay hardware costs per unit. The new performance dynamics and cost have extended the range of viable applications these days.

Market Research and Market Trends of Field Programmable Gate Array (FPGA) Ecosystem

FPGA As Cloud Server: IoT devices usually have limited processing power, memory size and bandwidth. The developers offer interfaces through compilers, tools, and frameworks. This creates effectiveness for the customer base and creates strong cloud products with increased efficiency which also included new machine learning techniques, Artificial Intelligence and big data analysis all in one platform. Web Service Companies are working to offer FPGAs in Elastic Compute Cloud (EC2) cloud environment. 

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Artificial Intelligence: As an order of higher magnitude performance per Watt than commercial FPGAs and (Graphical Processing Unit) GPUs in SOC search giant offers TPUs (Google’s Tensor Processing Units). AI demands for higher performance, less time, larger computation with more power proficient for deep neural networks. Deep neural network power-up the high-end devices. Google revealed that the accelerators (FGPAs) were used for the Alpha GO systems which is a computer developed by Google DeepMind that plays the board game Go.  CEA also offers an ultra-low power programmable accelerator called P-Neuro.

Photonic Networks for Hardware Accelerators: Hardware Accelerators normally need high bandwidth, low latency, and energy efficiency. The high performance computing system has critical performance which is shifted from the microprocessors to the communications infrastructure. Optical interconnects are able to address the bandwidth scalability challenges of future computing systems, by exploiting the parallel nature and capacity of wavelength division multiplexing (WDM). The multi-casted network uniquely exploits the parallelism of WDM to serve as an initial validation for architecture. Two FPGA boarded systems emulate the CPU and hardware accelerator nodes. Here FPGA transceivers implement and follow a phase-encoder header network protocol. The output of each port is individually controlled using a bitwise XNOR of port’s control signal. Optical packets are send through the network and execute switch and multicasting of two receive nodes with most reduced error

Low Power and High Data Rate FPGA: “Microsemi” FPGAs provides a non-volatile FPGA having 12.7 GB/s transceiver and lower poor consumption less than 90mW at 10 GB/s. It manufactured using a 28nm silicon-oxide-nitride-oxide-silicon nonvolatile process on standard CMOS technology. By this they address cyber security threats and deep submicron single event upsets in configuration memory on SRAM-based FPGA. These transceivers use cynical I/O gearing logic for DDR memory and LVDS. Cryptography research provides differential power analysis protection technology, an integrated physical unclonable function and 56 kilobyte of secure embedded non-volatile memory, the built-in tamper detectors parts and counter measures.

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Speeds up FPGA-in-the-loop verification: HDL Verifier is used to speed up FPGA-in-the-loop (FIL) verification. Faster communication between the FPGA board and higher clock frequency is stimulated by the FIL capabilities. This would increase the complexity of signal processing, control system algorithms and vision processing. For validation of the design in the system context simulate hardware implementation on an FPGA board. HDL Verifier automates the setup and connection of MATLAB and Simulink test environments to designs running on FPGA development boards. The R2016b has been released that allows engineers to specify a custom frequency for their FPGA system clock with clock rates up to five times faster than previously possible with FIL. This improves faster run-time. From MATLAB and Simulink is an easy way to validate hardware design within the algorithm development environment

Xilinx Unveils Revolutionary Adaptable Computing Product Category: Xilinx, Inc. which is leader in FGPAs, has recently announced a new product category which is named as Adaptive Compute Acceleration Platform (ACAP) and has the capabilities far beyond of an FPGA. An ACAP is a highly integrated multi-core heterogeneous compute platform that can be changed at the hardware level to adapt to the needs of a wide range of applications and workloads. ACAP has the capability of dynamic adaption during operation which enables it to deliver higher performance per-watt levels that is unmatched by CPUs or GPUs.

Lattice Releases Next-Generation FPGA Software for Development of Broad Market Low Power Embedded Applications: Lattice Semiconductor, launched its FPGA software recently. Lattice Radiant targeted for the development of broad market low power embedded applications. Device’s application expands significantly across various market segments including mobile, consumer, industrial, and automotive due to is rich set of features and ease-of-use, Lattice Radiant software’s support for iCE40 Ultra plus FPGAs. ICE40 Ultra Plus devices are the world’s smallest FPGAs with enhanced memory and DSPs to enable always on, distributed processing. The Lattice Radiant software is available for free download.

Who are the Major Players in market?

The companies referred in the market research report include Intel Inc, Microsemi, Lattice Semiconductor, Xilinx, Atmel, Quick Logic Corp., Red Pitaya, Mercury Computer, Nallatech Inc., Achronix Semiconductor Corporation, Acromag Inc., Actel Corp., Altera Corp.

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What is our report scope?

The report incorporates in-depth assessment of the competitive landscape, product market sizing, product benchmarking, market trends, product developments, financial analysis, strategic analysis and so on to gauge the impact forces and potential opportunities of the market. Apart from this the report also includes a study of major developments in the market such as product launches, agreements, acquisitions, collaborations, mergers and so on to comprehend the prevailing market dynamics at present and its impact during the forecast period 2017-2023.

All our reports are customizable to your company needs to a certain extent, we do provide 20 free consulting hours along with purchase of each report, and this will allow you to request any additional data to customize the report to your needs.

Key Takeaways from this Report

Evaluate market potential through analyzing growth rates (CAGR %), Volume (Units) and Value ($M) data given at country level – for product types, end use applications and by different industry verticals.

Understand the different dynamics influencing the market – key driving factors, challenges and hidden opportunities.

Get in-depth insights on your competitor performance – market shares, strategies, financial benchmarking, product benchmarking, SWOT and more.

Analyze the sales and distribution channels across key geographies to improve top-line revenues.

Understand the industry supply chain with a deep-dive on the value augmentation at each step, in order to optimize value and bring efficiencies in your processes. 

Get a quick outlook on the market entropy – M&A’s, deals, partnerships, product launches of all key players for the past 4 years. 

Evaluate the supply-demand gaps, import-export statistics and regulatory landscape for more than top 20 countries globally for the market. 

[nakshtechnology]

Why Choose the SINAMICS G120 Drive for Your Automation Needs? 

The importance and significance reliable, capable, and multi-purpose drive solutions are to the dynamic industrial automation industry. Siemens, the best performing in automation technology globally, offers the perfect solution with the SINAMICS G120 drive design. Designed for the needs of current industries, this extensive drive system guarantees the best possible performance while minimizing energy usage. This blog will explore the main characteristics, reasons why you will benefit from having one and how they are applied in SINAMICS G120. 

What is the SINAMICS G120? 

The SINAMICS G120 is a multipurpose drive system having integrated technological advancement with simple design structures for user application. User's applications in differential requirement from gradual transport systems on one hand up to more complex processing machinery on the other hand are taken care of through the modularity of this system. The flexibility characterizing the G120 series has yielded a wide market base because it has provided the user with the option of choosing only what is best suited based on one’s requirements. 

Key Features of the SINAMICS G120 Drive 

Modularity: The SINAMICS G120 drive is made up of separate power and control modules thus giving it unrivalled flexibility. At the same time, customization and maintenance are straightforward thanks to this modular approach resulting in minimal downtimes and effective operation. 

Advanced Control Functions: The G120 driver has advanced control algorithms that improve performance and accuracy, such as vector control, V/f control, and encoder less operations making it useful in diverse applications. 

Integrated Safety: Industrial safety is a crucial thing. Embedded safety features in SINAMICS G120 like Safe Torque Off (STO) and Safe Stop 1 (SS1), ensure safety for both operators and equipment. 

Energy Efficiency: The SINAMICS G120 drive helps to bring down operating costs with its ability to conserve power. It is a drive that can save energy because it can use power again by recycling. 

User-Friendly Interface: This drive has intuitive interfaces and configuration tools to make installation and operation easier. In the TIA Portal, SINAMICS Startdrive software is fully integrated to create a flawless user experience. 

Exploring the G120 Power Module 

The G120 Power Module is the core of the SINAMICS G120 drive. Its function is to convert the electric power supplied into the necessary driving motor forms. Available in different power rates, the G120 Power Module facilitates its use in combinations with motors of diverse sizes and for various tasks. 

Key Features of the G120 Power Module: 

High Efficiency: The power module works with high efficiency, managing energy reduction and performance enhancement. 

Robust Design: The G120 power module has been made so strong for under extremely harsh industrial conditions which is the reason for the guarantee of its consistent operation. 

Versatility: The power module is available in different setups and can be easily blended with various applications ranging from simple machines to complex systems. 

Applications of the SINAMICS G120 Drive 

SINAMICS G120 drive is a versatile solution that finds applications across a wide range of industries. Some common applications include: 

Conveyor Systems: This drive has exact control and is very energy efficient and is the best among the conveyor systems for manufacture and logics. 

Pumps and Fans: This product makes sure that pumps and fans perform well, and this enhances energy thrift and process management. 

Compressors: The efficiency and reliability of compressors in various industrial settings is improved by the drive’s advanced control functions. 

Mixers and Agitators: Its rugged design with accurate control means it can be applied in mixers and agitators for chemical and food processing industries. 

Conclusion: 

Siemens' SINAMICS G120 drive is a demonstration of dedication to innovation and excellence in automation technology. The SINAMICS G120 drive equally presents an essential part of advanced industries. It does this by having a modular design, advanced control functionalities, integrated safety functions as well as energy efficiency features. It has been designed to enhance conveyor systems efficiency, increase pump and fan performance and boost compressor efficiency. 

You can attain greater industrial performance and efficiency through the utilization of the G120 power unit’s immense power capacity and the SINAMICS G120 drive’s extensive functionalities. Engage with Siemens to investigate the potentialities in your automation systems. 

[tallman-robotics]

Linear Motion Solutions

Linear motion solutions refer to the various technologies and systems designed to provide controlled, precise linear movement. These solutions are used across a wide range of industries and applications, including industrial automation, robotics, machinery, and more.

Here are some key aspects of linear motion solutions:

Types of Linear Motion Systems: Ball screw systems,Lead screw systems,Linear motor systems,Belt-driven systems,Air/fluid bearing systems,Rack and pinion systems,Linear slide systems Key Components:, Linear actuators (e.g. ball screws, lead screws, linear motors),Linear guides (e.g. linear bearings, rails, slides),Drive mechanisms (e.g. stepper motors, servo motors),Control systems (e.g. motion controllers, drivers),Feedback sensors (e.g. encoders, limit switches) Design Considerations: Application requirements (e.g. load, speed, precision),Environmental factors (e.g. temperature, humidity, contaminants),Space constraints and mounting configurations,Integration with other systems and equipment,Maintenance and lubrication needs Common Applications: Industrial automation and robotics,CNC machines and machine tools,Semiconductor manufacturing equipment,Packaging and material handling systems,Medical devices and instrumentation,Test and measurement equipment,3D printing and additive manufacturing Trends and Advancements:,Increased use of linear motors for high-speed, high-accuracy applications,Integration of smart sensors and Industry 4.0 connectivity,Advancements in control algorithms and software,Developments in materials and lubrication for improved performance and reliability

You are welcome to watch more projects or visit our website to check other series or load down e-catalogues for further technical data.  Youtube: https://www.youtube.com/@tallmanrobotics Facebook: https://www.facebook.com/tallmanrobotics Linkedin: https://www.linkedin.com/in/tallman-robotics Read the full article

[gtrsimulator1]

Unveiling the Power and Precision of Direct Drive Wheels in Sim Racing

Direct drive wheels have become the crown jewel of sim racing setups, promising unparalleled realism, precision, and immersion for enthusiasts. In the realm of virtual racing, where every detail counts, these devices stand out as the pinnacle of technology and engineering. Let's delve into what makes Direct drive wheel so remarkable and why they are coveted by serious sim racers worldwide.

At its core, a direct drive wheel replaces the traditional belt or gear-driven mechanism with a direct connection between the motor and the steering wheel. This direct linkage eliminates the inherent slack and latency found in belt-driven or gear-driven systems, offering instant, precise feedback to the driver's inputs. The result is a level of responsiveness and fidelity that closely mirrors the feel of a real racing car.

One of the defining features of direct drive wheels is their sheer strength. Unlike their counterparts, which rely on gears or belts to transmit force, direct drive wheels harness the raw power of electric motors to deliver uncompromising torque directly to the wheel. This means that every nuance of the road surface, every bump, and every curb is faithfully conveyed to the driver's hands, allowing for unparalleled control and immersion.

Precision is another hallmark of direct drive wheels. With their high-resolution encoders and advanced control algorithms, these devices are capable of delivering incredibly accurate force feedback, allowing drivers to feel even the slightest change in grip or traction. This level of precision not only enhances the driving experience but also enables drivers to fine-tune their technique and push the limits of their performance.

Direct drive wheels also offer unmatched customization and flexibility. Most models allow users to adjust a wide range of parameters, such as force feedback strength, damping, and steering sensitivity, to suit their preferences and driving style. This level of customization empowers drivers to tailor their setup to their exact specifications, whether they prefer a more realistic driving experience or a more forgiving setup for casual racing.

Moreover, direct drive wheels are built to last. With their robust construction and premium components, these devices are designed to withstand the rigors of intense racing simulations and provide years of reliable service. While they may come with a higher price tag compared to other wheel options, their longevity and performance make them a worthwhile investment for serious sim racers.

In recent years, the popularity of direct drive wheels has surged, thanks in part to advancements in technology and increased accessibility. While once considered exotic and prohibitively expensive, these devices are now more affordable and widely available than ever before, making them accessible to a broader audience of sim racing enthusiasts.

However, it's essential to note that direct drive wheels are not without their drawbacks. Their higher cost and complexity may deter casual users or those on a budget, while their immense strength can be overwhelming for inexperienced drivers. Additionally, the increased force feedback may require a more robust rig setup to prevent unwanted flex or vibration.

[spookysaladchaos]

Biped Robot, Global Top Eight Players Rank and Total Market Size Forecast 2023-2029

Biped Robot Market Summary

In humanoid robots, there are usually two types according to their shape: biped humanoid robots and wheeled humanoid robots. Different from the biped robot driving method, the wheeled robot is mainly driven by the steering wheel and wheels. It has a simple structure, convenient control, and can realize simple forward, turning and backward functions. A biped robot is a bionic type of robot whose structure is similar to that of a human biped. It can realize bipedal walking and related actions of the robot, mainly through the servo system (motor + drive + encoder) to drive the joints, and the servo system is also The core component of motion control. At present, biped robots on the market can be divided into small biped robots and large biped robots.

According to the new market research report "Global Biped Robot Market Report 2023-2029", published by QYResearch, the global Biped Robot market size is projected to reach USD 698 million by 2029, at a CAGR of 17% during the forecast period.

Figure.   Global Biped Robot Market Size (US$ Million), 2018-2029

Based on or includes research from QYResearch: Global Biped Robot Market Report 2023-2029.

Market Drivers:

1. Core driver: policy support. The support of national policies is always the core driving factor for the development of the industry. The national policy support for biped robots can speed up the penetration of robots in applications, and will also attract funds to invest in the robotics industry, thereby improving the R&D and innovation system of enterprises.

2. The second driver: terminal application. Bipedal robots are used downstream in education, medical care, retail and other scenarios. The growth in application demand is conducive to the development of bipedal robots.

Restraint:

At present, the main obstacles to the development of bipedal robots are funds and technical talents. The robot industry belongs to the high-tech industry, and the biped robot integrates multiple technologies, which also means that its manufacturing cost is high, which limits the commercialization process of biped robots to a certain extent.

Opportunity:

Opportunities and favorable factors for the development of the bipedal robot industry are mainly reflected in three aspects: policy support, breakthrough of technical bottlenecks, and market size.

This year, many regions have introduced policies for bipedal humanoid robots, such as Beijing, Shenzhen, Shanghai and other places. The common point of the policies is to accelerate the deployment of humanoid robots, which is a great benefit to the development of bipedal robots.

In addition, the Chinese market is huge. In the industrial robot market, China’s consumption has ranked first for several consecutive years. Bipedal robots belong to a subdivision of industrial robots. The rapid development of industrial robots and the growing market size have also brought huge development opportunities to bipedal robots.

Figure.   Biped Robot, Global Market Size, The Top Five Players Hold 50% of Overall Market

Based on or includes research from QYResearch: Global Biped Robot Market Report 2023-2029.

Globally, the major manufacturers of bipedal robots include UBTECH, Leju, SoftBank Robotics, Robo Garage, DS Technologies, Agility Robotics, Hanson Robotics and PAL Robotics, among which the top five manufacturers account for approximately 65% of the market share.

At present, the world's core commercial manufacturers are mainly distributed in China and the United States. Among them, Chinese companies Youbixuan and Leju mainly focus on small bipedal robots, while large-scale robot companies that have not commercialized include Xiaomi and Unitree Robotics; foreign companies include Boston Dynamics, Honda, Toyota, Tesla, Sanctuary AI, 1X Technologies and Figure AI, etc.

Figure.   Biped Robot, Global Market Size, Split by Product Segment

Based on or includes research from QYResearch: Global Biped Robot Market Report 2023-2029.

In terms of product types, small biped robots are currently the most important subdivided product, accounting for about 80% of the market in 2022. From the perspective of product type and technology, small bipedal robots occupy a large market share due to their low manufacturing cost and high degree of commercialization. Most of them are used in education and entertainment fields. Large-scale bipedal robots are costly and difficult to produce, and their selling prices are quite different from small ones. Currently, due to cost and technical issues, terminal applications are relatively limited. Although enterprises can produce them, their commercialization is not high. With the development of future technology, AI and deep learning technology will become more mature, and large-scale bipedal robots are expected to be controlled on the cost side, thereby achieving large-scale production and sales. It is estimated that by 2029, the market size of large biped robots is expected to dominate, and the CAGR 2023-2029 will reach 42%.

Figure.   Biped Robot, Global Market Size, Split by Application Segment

Based on or includes research from QYResearch: Global Biped Robot Market Report 2023-2029.

In terms of product applications, education and entertainment are currently the main sources of demand, accounting for approximately 65% of the market share in 2022. Humanoid robots (wheeled and bipedal) are robots designed and manufactured to imitate human form and behavior. They have a human-like appearance, can adapt to human living and working environments, replace or assist humans in completing various tasks, and can It expands human capabilities in many aspects and has broad application prospects in services, medical care, education, entertainment and other fields. Among them, wheeled humanoid robots are more widely used than bipedal robots because of their simple structure and convenient control.

Bipedal robots are currently mainly used in education, entertainment, research and space exploration, and a small number of them are used in the medical and logistics fields.

Figure.   Biped Robot, Global Market Size, Split by Region (Production)

Based on or includes research from QYResearch: Global Biped Robot Market Report 2023-2029.

As far as the production side is concerned, currently commercialized bipedal robots are mainly produced in China and Japan, and other regions are mainly the United States and Europe. Among them, China's output accounts for a large share, reaching 59% in 2022; followed by Japan, accounting for 32%. In the past two years, Chinese, American, Canadian and European companies have continuously poured into the bipedal robot market and launched new products. For example, China: Xiaomi’s CyberOne, Unitree’s Unitree H1, the United States: Tesla’s Optimus, Figure AI’s Figure 01, Canada: Sanctuary AI’s Phoenix, etc. In the future, the share of North American and European countries is expected to exceed 10%.

Figure.   Biped Robot, Global Market Size, Split by Region

Based on or includes research from QYResearch: Global Biped Robot Market Report 2023-2029.

As far as the consumption area is concerned, it is currently mainly North America, Europe, China, Japan, India and Southeast Asia. Among them, China, Japan and North America have a market share of more than 85%. With the development of China's robot industry, the volume of the robot market will continue to expand, which is expected to improve the biped robot industry technology and reduce costs. It is estimated that by 2029, China's biped robot market share will reach 60%.

About The Authors

Junping Yang - Lead Author

Email: yangjunping@qyresearch.com

Junping Yang is a technology & market senior analyst specializing in semiconductor devices, materials, and equipment. Yang has 9 years’ experience in semiconductor and focuses on ICs, semiconductor materials, package & testing, power semiconductor (IGBT, SiC, diode, MOSFET, modules and discrete), compound semiconductor (SiC, GaN, etc.), power, RF, optoelectronics, ceramic substrates (HTCC, LTCC, DBC, AMB, DPC, DBA), CMP, equipment & parts (wafer transfer robot, EFEM/Sorter, heaters, etc.). He is engaged in the development of technology and market reports and is also involved in custom projects.

About QYResearch

QYResearch founded in California, USA in 2007.It is a leading global market research and consulting company. With over 16 years’ experience and professional research team in various cities over the world QY Research focuses on management consulting, database and seminar services, IPO consulting, industry chain research and customized research to help our clients in providing non-linear revenue model and make them successful. We are globally recognized for our expansive portfolio of services, good corporate citizenship, and our strong commitment to sustainability. Up to now, we have cooperated with more than 60,000 clients across five continents. Let’s work closely with you and build a bold and better future.

QYResearch is a world-renowned large-scale consulting company. The industry covers various high-tech industry chain market segments, spanning the semiconductor industry chain (semiconductor equipment and parts, semiconductor materials, ICs, Foundry, packaging and testing, discrete devices, sensors, optoelectronic devices), photovoltaic industry chain (equipment, cells, modules, auxiliary material brackets, inverters, power station terminals), new energy automobile industry chain (batteries and materials, auto parts, batteries, motors, electronic control, automotive semiconductors, etc.), communication industry chain (communication system equipment, terminal equipment, electronic components, RF front-end, optical modules, 4G/5G/6G, broadband, IoT, digital economy, AI), advanced materials industry Chain (metal materials, polymer materials, ceramic materials, nano materials, etc.), machinery manufacturing industry chain (CNC machine tools, construction machinery, electrical machinery, 3C automation, industrial robots, lasers, industrial control, drones), food, beverages and pharmaceuticals, medical equipment, agriculture, etc.

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Stepper Motors and Accessories: A Journey into the Heart of Electronics

In the captivating realm of electronics, where innovation dances hand in hand with precision, stepper motors and accessories take center stage, orchestrating a symphony of controlled movements and unparalleled accuracy. These electronic marvels are the unsung heroes behind the seamless functioning of countless devices, from 3D printers to CNC machines, breathing life into the world of automation.

Stepping into the Basics

Let’s kick off our exploration by demystifying the fundamental concept of stepper motors. Unlike their counterparts, stepper motors operate by dividing a full rotation into a series of discrete steps. Each step corresponds to a precise angle, allowing for controlled and repeatable movements. It’s like a carefully choreographed dance, where every step is intentional and contributes to the overall performance.

Why the Fuss About Stepper Motors?

The charm of stepper motors lies in their ability to provide precise control over movement, making them indispensable in applications where accuracy is non-negotiable. Picture this: a 3D printer creating intricate designs layer by layer or a robotic arm executing complex tasks with surgical precision. That’s the magic of stepper motors at play.

But what makes them tick?

Enter accessories. These unsung accomplices enhance the capabilities of stepper motors, turning them from mere components into powerhouses of functionality. Accessories like drivers, controllers, and encoders act as the supporting cast, ensuring that the stepper motor’s performance is nothing short of spectacular.

Drivers: The Conductors of the Orchestra

If stepper motors are the musicians, drivers are the conductors ensuring harmony in the symphony of motion. Stepper motor drivers translate digital signals from a controller into the precise electrical pulses needed to drive the motor. Imagine a conductor guiding each musician, dictating when and how to play their instruments. That’s the role of a stepper motor driver in this electronic orchestra.

Controllers: The Puppet Masters

In the grand scheme of automation, controllers play the role of puppet masters, pulling the strings to choreograph intricate movements. These electronic maestros interpret input commands and translate them into a sequence of steps for the stepper motor. Whether it’s guiding the movements of a 3D printer or navigating the path of a CNC machine, controllers are the brains behind the operation.

Encoders: The Guardians of Precision

In the pursuit of perfection, encoders act as guardians, ensuring that the stepper motor follows its prescribed path with unwavering accuracy. These devices provide real-time feedback on the motor’s position, allowing for adjustments to correct any deviations. Think of them as the navigators ensuring that the ship stays on course even in the stormiest seas.

As we wrap up our journey into the world of stepper motors and accessories, it’s clear that these electronic virtuosos are the unsung heroes shaping the landscape of precision and control. From the rhythmic dance of a 3D printer to the orchestrated movements of a CNC machine, stepper motors and their trusted accessories are the heartbeat of innovation in the realm of electronics. So, the next time you marvel at the seamless operation of a high-tech device, take a moment to appreciate the behind-the-scenes brilliance of stepper motors and accessories — the true architects of controlled motion in the electronic symphony.

[david843346]

Rotary Encoder Market: Global Demand Analysis & Opportunity Outlook 2036

Research Nester’s recent market research analysis on “Rotary Encoder Market: Global Demand Analysis & Opportunity Outlook 2036” delivers a detailed competitor’s analysis and a detailed overview of the global rotary encoder market in terms of market segmentation by type, product, application, end-user industry, and by region.

Increasing Industrialization and Digitization to Promote Global Market Share of Rotary Encoder

The market is predicted to increase moderately as a result of the Industry 4.0 revolution and digitization, which have further expedited the adoption of automation across a number of industries. Industry 4.0 persuaded OEMs to include IoT in their operations due to the consistent increase in IoT usage and digital transformation occurring across several industries. For instance, according to the International Data Corporation's (IDC) Worldwide Semiannual Internet of Things Expenditure Guide, European investment in the Internet of Things (IoT) exceeded USD 202 billion in 2021. It is expected to increase by double digits through 2025.

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In addition to these, Governments everywhere are promoting the adoption of various automation technologies to support the structural expansion of industrial firms. Governments across the globe focus on the manufacturing sectors since they are essential to this progress. This is expected to promote market expansion overall by increasing the usage of industrial robots.

Some of the major growth factors and challenges that are associated with the growth of the global rotary encoder market are:

Growth Drivers:

Surge in Technological Developments and High Accuracy Could Strengthen Market Growth

Rising Automotive Industry

Challenges:

Lack of product differentiation is one factor hindering the growth of the rotary encoder market. Because rotary encoders are used in such large quantities in the electronics, aerospace, automotive, and other industries, customers purchase them in bulk. Rotary encoders can have a wide range of functions and applications. Due to the wide variety of huge enterprises offering similar technology items, consumers have many options. In order to compete with larger manufacturers for the high volume of these products, manufacturers are under pressure to reduce their pricing. This is troublesome because it puts pressure on manufacturing prices. Encoders encounter a number of issues and constraints that reduce their capacity to endure competition because of their few brittle parts and possible complexity and potential error causes that could lead to the inaccuracy are some of the major factors anticipated to hamper the global market size of rotary encoder.

By application, the global rotary encoder market is segmented into metal forming & fabrication, servo motor, elevator industry, machine tool and material handling. The machine tool segment is to garner the highest revenue by the end of 2036 by growing at a significant CAGR over the forecast period. In machine tool applications, rotary encoders are used to accomplish precise sensing and positioning. A machine can determine the exact commutation angle and axis alignment. Rotating encoders improve system precision and enable optimal machine performance. It is heavily used in this application for these reasons. It is anticipated that the robust adoption rate and increasing demand will drive the robotics segment's notable expansion. The International Federation of Robotics (IFR) projects that between 2020 and 2022, factories globally will deploy close to 2 million industrial robots. These factors should boost demand for rotary encoders because of their widespread application in robotics.

By region, the Europe rotary encoder market is to generate the highest revenue by the end of 2036. Industrial robotic applications are one of the many potential markets for encoders, and this increase is projected to boost the market growth in the region. Automation in many industries in Europe may eventually lead to a rise in the need for robots, which will also raise the need for rotary angle sensors. Another dynamic area that has a lot of promise for the increase in encoder demand over the course of the projection period is the electronic sector.

Access our detailed report at:

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AC Servo Motor Market Size Global Forecast to 2028

Global AC Servo Motor Market Report from AMA Research highlights deep analysis on market characteristics, sizing, estimates and growth by segmentation, regional breakdowns & country along with competitive landscape, player’s market shares, and strategies that are key in the market. The exploration provides a 360° view and insights, highlighting major outcomes of the industry. These insights help the business decision-makers to formulate better business plans and make informed decisions to improved profitability. In addition, the study helps venture or private players in understanding the companies in more detail to make better informed decisions. Some are the key & emerging players that are part of coverage and have being profiled are Siemens AG (Germany), ABB (Switzerland), Rockwell Automation, Inc. (United States) , KEB Automation KG (Germany), Bosch Rexroth AG (Germany), Mitsubishi Electric Corporation (Japan), FANUC CORPORATION (Japan) , The Yaskawa Electric Corporation (Japan), Schneider Electric (France)  , Panasonic Corporation (Japan). Get Free Exclusive PDF Sample Copy of This Research @ https://www.advancemarketanalytics.com/sample-report/22956-global-ac-servo-motor-market AC servo motor includes an encoder which is used by the controllers to give feedback as well as closed-loop control. AC motor can be located too high accuracy as well as controlled accurately as necessary for the applications. These motors have superior designs in order to achieve better torque. The AC servo motor applications mainly include robotics, automation, CNC equipment, and many more applications. This has led to significant growth of the global AC servo motor market in the forecast period.

The titled segments and sub-section of the market are illuminated below: by Type (Positional Rotation Servo Motor, Continuous Rotation Servo Motor, Linear Servo Motor), Industry Verticals (Automotive & Transportation, Semiconductor & Electronics, Food Processing, Textile, Petrochemicals, Packaging, Pharmaceuticals & Healthcare, Printing & Paper, Others (Energy & Power), Communication Protocol (Fieldbus, Industrial Ethernet, Wireless), Phase Type (2 Phase, 3 Phase), Voltage Range (Low-Voltage Servo Motors (Up to 690v), Medium-Voltage Servo Motors (Above 690v))

Market Trends:

Industrial Revolution 4.0

Opportunities:

Developing Regions for Servo Motors

Enhanced Encoders to Create New Possibilities in the Motors Market

Market Drivers:

Rapid Development & Growth in Automation

Increase in Acceptance of Energy Effective International Standards

Rising Easy Usage & Integration of Motion Control Components in Motors

Global AC Servo Motor market report highlights information regarding the current and future industry trends, growth patterns, as well as it offers business strategies to help the stakeholders in making sound decisions that may help to ensure the profit trajectory over the forecast years. Region Included are: North America, Europe, Asia Pacific, Oceania, South America, Middle East & AfricaCountry Level Break-Up: United States, Canada, Mexico, Brazil, Argentina, Colombia, Chile, South Africa, Nigeria, Tunisia, Morocco, Germany, United Kingdom (UK), the Netherlands, Spain, Italy, Belgium, Austria, Turkey, Russia, France, Poland, Israel, United Arab Emirates, Qatar, Saudi Arabia, China, Japan, Taiwan, South Korea, Singapore, India, Australia and New Zealand etc. Have Any Questions Regarding Global AC Servo Motor Market Report, Ask Our Experts@ https://www.advancemarketanalytics.com/enquiry-before-buy/22956-global-ac-servo-motor-market Points Covered in Table of Content of Global AC Servo Motor Market:

Chapter 01 – AC Servo Motor Executive Summary

Chapter 02 – Market Overview

Chapter 03 – Key Success Factors

Chapter 04 – Global AC Servo Motor Market - Pricing Analysis

Chapter 05 – Global AC Servo Motor Market Background

Chapter 06 -- Global AC Servo Motor Market Segmentation

Chapter 07 – Key and Emerging Countries Analysis in Global AC Servo Motor Market

Chapter 08 – Global AC Servo Motor Market Structure Analysis

Chapter 09 – Global AC Servo Motor Market Competitive Analysis

Chapter 10 – Assumptions and Acronyms Chapter 11 – Research Methodology Read Detailed Index of full Research Study at @https://www.advancemarketanalytics.com/reports/22956-global-ac-servo-motor-market Thanks for reading this article; you can also get individual chapter wise section or region wise report version like North America, Middle East, Africa, Europe or LATAM, Southeast Asia. Contact US : Craig Francis (PR & Marketing Manager) AMA Research & Media LLP Unit No. 429, Parsonage Road Edison, NJ New Jersey USA – 08837 Phone: +1 201 565 3262, +44 161 818 8166 sales@advancemarketanalytics.com

[stepperonline52]

Permanent magnet stepper motor maintenance and maintenance methods

1.Brief introduction of permanent magnet stepper motor ‌ Permanent magnet stepper motor ‌ is a type of motor whose working principle is based on the interaction between permanent magnets and electromagnetic coils. This motor usually consists of a permanent magnet rotor and several stators, in which a group of permanent magnets are fixed on the permanent magnet rotor, and several electromagnetic coils are distributed on the stator. The constant magnetic field generated by the permanent magnet interacts with the temporary magnetic field generated by the current passing through the stator electromagnetic coil, resulting in the occurrence of a rotating magnetic field. By changing the excitation sequence and current direction of the electromagnetic coils on the stator, the steering and stepping motion of the rotating magnetic field can be achieved. Each time the excitation state of the electromagnetic coil is changed, the permanent magnet rotor will rotate a fixed angle, which is called the step angle. In order to achieve stepping motion, the permanent magnet stepper motor usually needs to control the direction and size of the current through the control circuit and driver.

2.Methods to improve the efficiency of permanent magnet stepper motors 1.Optimize electromagnetic design ‌: Select the appropriate magnetic circuit structure, stator winding form and magnetic field distribution to achieve the best effect. At the same time, consider factors such as the magnetic energy loss and copper loss of the motor to make reasonable comprehensive optimization. 2.Optimize mechanical design: In mechanical design, factors such as rotor structure, bearings, vibration reduction, etc. should be considered to reduce mechanical loss and friction loss. 3.Optimize control strategy: Use efficient control algorithms such as vector control and direct torque control to reduce rotor loss and copper loss. 4.Optimize material selection: Select materials with high magnetic permeability and low hysteresis loss to reduce magnetic energy loss and copper loss. 5.Reduce motor loss: When the stepper motor is enabled, if the motor stops running, its shaft retention does not require full circuit operation under most working conditions. Therefore, the power consumption can be reduced by turning on the half-current function of the stepper driver. Specifically, when the motor is in a stopped state, the driver automatically switches to a half-current state, reducing the current in the winding, thereby reducing power consumption. 6.Use direct-drive permanent magnet stepper motors: Avoid using mechanical transmission mechanisms such as worm gear reducers to improve equipment efficiency. Direct-drive permanent magnet stepper motors can provide higher energy efficiency.

‌3.Control methods of permanent magnet stepper motors 1.Pulse control‌: This is a traditional stepper motor position and speed control method, in which the rotation distance depends on the number of pulses and the speed depends on the pulse frequency. Common pulse control methods include: Pulse direction type‌: When the pulse input jumps from high to low (falling edge), the direction input is low (or floating), and the motor rotates one step in the clockwise direction; when the direction input is high, the motor rotates one step in the counterclockwise direction. The direction definition can be configured by software. CW/CCW pulse type‌: When the CW pulse input jumps from high to low (falling edge), the motor rotates one step in the clockwise direction; when the CCW pulse input jumps from high to low (falling edge), the motor rotates one step in the counterclockwise direction. The direction definition can also be configured by software. ‌A/B orthogonal pulse type‌: The motor rotates according to the signal fed back to the driver from a dual-channel incremental master encoder. The direction is determined by which channel leads the other channel. 2.Analog control: Stepper drives support speed control and position control based on analog signals, and stepper servos also support torque mode based on analog signal control. 3.Fieldbus control: Supports various industrial fieldbuses, including RS-485, Modbus, CAN, Ethernet, and EtherCAT. 4.Program resident mode: Complete complex single-axis motion control by executing stored programs.

4.Maintenance and care of permanent magnet stepper motors 1.Regular maintenance: Maintain the daily maintenance of permanent magnet motors to keep them in a relatively new state. This includes regular replacement of electronic components, cleaning of the machine surface, and prevention of scratches. When operating the machine, use it according to regulations, do not overload it, perform regular maintenance after use, and remove part of the machine for storage if it is not used for a long time to avoid various loose phenomena and related failures of the machine. 2.Environmental adaptability: Ensure that the stepper motor works in a dry, well-ventilated environment without corrosive gas and dust pollution. Avoid installing the motor in an environment that is too humid, has corrosive gases, has severe dust, and has high or low temperatures. Special cases require consultation with the manufacturer. 3.Cleaning and lubrication: After the stepper motor has been operated for a period of time, it will be stained with dust, oil and other debris, affecting normal operation. The surface of the machine should be wiped and the oil should be washed away, and lubrication should be regularly filled with oil to maintain the speed and stability of operation. Install a cover to prevent dust from entering and damaging the internal parts of the motor. 4.Temperature control: Excessive temperature of the stepper motor will cause the magnetic material to demagnetize, thereby reducing the torque or even losing steps. Therefore, the surface temperature of the motor should be controlled within the allowable range. Generally speaking, the demagnetization point of magnetic materials is above 130 degrees Celsius, and some are even as high as 200 degrees Celsius, so it is completely normal for the surface temperature of the stepper motor to be 80-90 degrees Celsius. 5.Installation and adjustment: Check the appearance of the motor before installation and replace damaged parts. Keep the axial direction without obvious deviation during installation, and adjust it when necessary. After disassembly, clean, derust and oil it to ensure that the machine base accuracy meets the requirements. 6.Power supply and wiring: Connect correctly according to the drawings or instructions, and do not arbitrarily modify, disassemble or change the motor working voltage. Check whether the power supply voltage meets the rated voltage of the motor, ensure that the power supply is grounded reliably, and the wires are laid neatly to avoid crossing unnecessary wires. Through the above measures, the service life of the permanent magnet stepper motor can be effectively extended, the cost of maintenance and replacement can be reduced, and the accuracy and stability of the machine can be guaranteed to meet the needs of various application scenarios.